Results 21 to 30 of about 3,211,731 (245)
Semantic Adversarial Attacks on Face Recognition Through Significant Attributes
International Journal of Computational Intelligence Systems, 2023 Face recognition systems are susceptible to adversarial attacks, where adversarial facial images are generated without awareness of the intrinsic attributes of the images in existing works. They change only a single attribute indiscriminately.
Yasmeen M. Khedr, Yifeng Xiong, Kun He
doaj +1 more source
Comparative Research on Application of Adversarial Samples for End-to-End Speaker Identification [PDF]
Jisuanji gongcheng, 2021 In order to explore the security threats and attack effects of the adversarial samples on the end-to-end speaker identification system, this paper analyzes five white box algorithms(FGSM, JSMA, BIM, C&W, PGD) and two black box algorithms(ZOO, HSJA ...
LIAO Junfan, GU Yijun, ZHANG Peijing, LIAO Qian
doaj +1 more source
An Optimized Black-Box Adversarial Simulator Attack Based on Meta-Learning
Entropy, 2022 Much research on adversarial attacks has proved that deep neural networks have certain security vulnerabilities. Among potential attacks, black-box adversarial attacks are considered the most realistic based on the the natural hidden nature of deep ...
Zhiyu Chen +7 more
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Cubicle: A family of space‐hard ciphers for IoT
IET Information Security, 2023 As IoT has increasingly evolved in recent years, it has become more important to ensure security on IoT devices. Many of such devices are under the threat of attacks in the beyond black‐box model.
Rentaro Shiba +3 more
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Empirical Perturbation Analysis of Two Adversarial Attacks: Black Box versus White Box
Applied Sciences, 2022 Through the addition of humanly imperceptible noise to an image classified as belonging to a category ca, targeted adversarial attacks can lead convolutional neural networks (CNNs) to classify a modified image as belonging to any predefined target class ...
Raluca Chitic +2 more
doaj +1 more source
Boosting Targeted Black-Box Attacks via Ensemble Substitute Training and Linear Augmentation
Applied Sciences, 2019 These years, Deep Neural Networks (DNNs) have shown unprecedented performance in many areas. However, some recent studies revealed their vulnerability to small perturbations added on source inputs.
Xianfeng Gao +4 more
doaj +1 more source
VBSM: VCC-Based Black Box Service Model with Enhanced Data Integrity
Information, 2014 Recently, intelligent transport systems have been applied to vehicle cloud environments. Such technology is especially useful for the systematic management of road traffic.
Won Min Kang +2 more
doaj +1 more source
IEEE Open Journal of Intelligent Transportation Systems, 2021 Security attacks on intelligent transportation systems (ITS) may result in life-threatening situations. Combining deep neural networks with reinforcement learning (RL) models called DRL shows promising results when applied to urban Traffic Signal Control
Ammar Haydari +2 more
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Understanding Black-Box Attacks Against Object Detectors from a User's Perspective [PDF]
, 2022 Due to recent developments in object detection systems, and the realistic threat of black-box adversarial attacks on object detector models, we argue the need for a contextual understanding of the attacks from the users’ perspective.
Li, Jingyue +2 more
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Back in Black: A comparative evaluation of recent state-of-the-art black-box attacks [PDF]
, 2021 The field of adversarial machine learning has experienced a near exponential growth in the amount of papers being produced since 2018. This massive information output has yet to be properly processed and categorized.
Mahmood, R. (Rigel) +7 more
core +2 more sources